Similarity comprehensive evaluation of humanoid robot arm motion

A suitable comprehensive evaluation method for similarity comprehensive evaluation of humanoid motion(mainly to robotic arm) is proposed.For different robotic arms, a static comprehensive evaluation model is established by projection pursuit evaluation based on indexes of humanoid robot arm motion in robotics and ergonomics field. Based on projection pursuit evaluation with timing information entropy and time degrees, a dynamic comprehensive evaluation method is proposed by linear weighting to each time's static model's indexes weight according to timing weighted vectors. Through comparing similarity comprehensive evaluation result based on static and dynamic comprehensive evaluation model, the results show that similarity based on dynamic comprehensive evaluation model is high. By comparing reliability, similarity and dispersion of static and dynamic comprehensive evaluation models, the results show that dynamic comprehensive evaluation result has better accuracy, stability and lower dispersion, and the result is more reasonable and real. Therefore, the dynamic comprehensive evaluation method proposed in this paper is more suitable for similarity comprehensive evaluation of humanoid robot arm motion.

A fingerprint identification algorithm by clustering similarity

This paper introduces a fingerprint identification algorithm by clustering similarity with the view to overcome the dilemmas encountered in fingerprint identification. To decrease multi-spectrum noises in a fingerprint, we first use a dyadic scale space (DSS) method for image enhancement. The second step describes the relative features among minutiae by building a minutia-simplex which contains a pair of minutiae and their local associated ridge information, with its transformation-variant and invariant relative features applied for comprehensive similarity measurement and for parameter estimation respectively. The clustering method is employed to estimate the transformation space. Finally, multi-resolution technique is used to find an optimal transformation model for getting the maximal mutual information between the input and the template features. The experimental results including the performance evaluation by the 2nd International Verification Competition in 2002 (FVC2002), over the four fingerprint databases of FVC2002 indicate that our method is promising in an automatic fingerprint identification system (AFIS).